Why is "Physics-informed neural networks" trending?

Search Interest Perspective

• Physics-informed AI could accelerate development of controlled-release drug patches, bandages - Brown University
• Automatic network structure discovery of physics informed neural networks via knowledge distillation - Nature
• Teaching neural networks where errors matter - EurekAlert!
• Modeling the Crustal Magnetic Field of Mars With Physics‐Informed Neural Networks - AGU Publications
• Learning Droplet Dynamics on Rough Unstructured Surfaces Using Physics-Informed Neural Networks (Student Abstract) | Proceedings of the AAAI Conference on Artificial Intelligence - The Association for the Advancement of Artificial Intelligence
• On the Possibility of Small Networks for Physics-Informed Learning - towardsdatascience.com
• Correction: WF-PINNs: solving forward and inverse problems of burgers equation with steep gradients using weak-form physics-informed neural networks - Nature
• A Multi-Objective Optimization Framework for Adaptive Weighting in Physics-Informed Machine Learning - The Association for the Advancement of Artificial Intelligence
• Reconstruction of Magnetohydrodynamic Reconnection Structures by Physics-Informed Neural Networks (PINNs) - AGU Publications
• Evaluating physics informed neural networks for water contamination risk prediction and environmental sustainability - Nature
• Physics-Informed Approach for Exploratory Hamilton–Jacobi–Bellman Equations via Policy Iterations - The Association for the Advancement of Artificial Intelligence
• Unsupervised spectra information extraction using physics-informed neural networks in the presence of non-linearities and multi-agent problems - Nature
• SSTODE: Ocean-Atmosphere Physics-Informed Neural ODEs for Sea Surface Temperature Prediction - The Association for the Advancement of Artificial Intelligence
• Resolving energy transfer dynamics in Eu²⁺-activated multi-site phosphors via metaheuristic optimization and physics-informed neural networks - Nature
• Physics-informed neural networks for predicting the surface temperature of carbon fiber reinforced polymers under laser irradiation - Nature
• Physics-informed neural network with weighted loss and hard constraints for hyperbolic conservation laws - Nature
• WF-PINNs: solving forward and inverse problems of burgers equation with steep gradients using weak-form physics-informed neural networks - Nature
• Automated design for physics-informed modeling with convolutional neural networks - Nature
• Analytical and numerical solutions of MABC fractional advection dispersion models by utilizing the modified physics informed neural networks with impacts of fractional derivative - Nature
• Advancing Physical Understanding with Interpretable Machine Learning - American Physical Society
• Physics-Informed Emulation of Systemic Circulation for Fast Parameter Estimation and Uncertainty Quantification - Wiley Online Library
• Fast electromagnetic field simulation using a current-density- based physics-informed neural network - Nature
• Prediction of coal and gas outbursts based on physics informed neural networks and traditional machine learning models | Scientific Reports - Nature
• Gupta and Colleagues Introduces QPINN Framework for Solving Integro and Fractional PDEs - Quantum Zeitgeist
• Hybrid physics-informed artificial intelligence for high-fidelity modeling and optimization of electrical systems - Frontiers
• Performance analysis of a three-dimensional micromixer with baffles using a flexible physics-informed neural network - Nature
• Automating PINN-based kinematic resolution of robotic joints using robotic process automation frameworks - Frontiers
• Inverse solution of process parameters in gear grinding using hierarchical bayesian physics informed neural network (HBPINN) - Nature
• New AI techniques to solve complex equations in physics - EurekAlert!
• AI-driven integration for deeper subsurface insights - GeoExpro
• Mapping the Glymphatic System with AI - Neuroscience News
• Deep neural networks enable accurate pricing of American options under stochastic volatility - EurekAlert!
• Thermodynamically consistent modeling of granular soils using physics-informed neural networks - Nature
• Physics-informed hybrid reinforcement learning for estimating lithium-ion battery state of health - Nature
• A streamlined approach for probabilistic pavement life-cycle performance prediction via physics-informed neural networks - Wiley Online Library
• Physics-informed machine learning-based real-time long-horizon temperature fields prediction in metallic additive manufacturing - Nature
• Efficient PINNs via multi-head unimodular regularization of the solutions space | Communications Physics - Nature
• ThoR: A Motion-Dependent Physics-Informed Deep Learning Framework with Constraint-Centric Theory of Functional Connections for Rainfall Nowcasting - Nature
• Physics-informed residual learning with spatiotemporal local support for inverse ECG reconstruction - Nature
• Information-distilled physics informed deep learning for high order differential inverse problems with extreme discontinuities - Nature
• Trainable embedding quantum physics informed neural networks for solving nonlinear PDEs - Nature
• Improving generalization ability of deep-learning-based ODE solvers using continuous dependence - Nature
• h -Analysis and data-parallel physics-informed neural networks - Nature
• Quantifying local and global mass balance errors in physics-informed neural networks - Nature
• Strategies for multi-case physics-informed neural networks for tube flows: a study using 2D flow scenarios - Nature
• Physics-informed neural networks for modeling physiological time series for cuffless blood pressure estimation - Nature
• Enhancing convergence speed with feature enforcing physics-informed neural networks using boundary conditions as prior knowledge - Nature
• Modeling global surface dust deposition using physics-informed neural networks - Nature
• Physics-Informed Neural Networks for Estimating a Continuous Form of the Soil Water Retention Curve From Basic Soil Properties - AGU Publications
• Physics informed neural networks for fluid flow analysis with repetitive parameter initialization - Nature
• Wavelets based physics informed neural networks to solve non-linear differential equations - Nature
• Physics-informed neural networks with hybrid Kolmogorov-Arnold network and augmented Lagrangian function for solving partial differential equations | Scientific Reports - Nature
• Physics-Informed Neural Networks Trained With Time-Lapse Geo-Electrical Tomograms to Estimate Water Saturation, Permeability and Petrophysical Relations at Heterogeneous Soils - AGU Publications
• Investigating molecular transport in the human brain from MRI with physics-informed neural networks - Nature
• Predicting 3D soft tissue dynamics from 2D imaging using physics informed neural networks - Nature
• Physics-informed neural networks for robust equivalent damping parameter inversion and fault diagnosis in gas-insulated switchgear vibration systems - Nature
• Affine transformations accelerate the training of physics-informed neural networks of a one-dimensional consolidation problem - Nature
• Number Theoretic Accelerated Learning of Physics-Informed Neural Networks - The Association for the Advancement of Artificial Intelligence
• Magnetic field mapping of inaccessible regions using physics-informed neural networks - Nature
• Physics-Informed Neural Networks for Fault Slip Monitoring: Simulation, Frictional Parameter Estimation, and Prediction on Slow Slip Events in a Spring-Slider System - AGU Publications
• DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation - The Association for the Advancement of Artificial Intelligence
• Physics-informed neural networks for solving time-dependent mode-resolved phonon Boltzmann transport equation - Nature
• Physics-informed neural networks for predicting gas flow dynamics and unknown parameters in diesel engines - Nature
• Rapid Permeability Upscaling of Digital Porous Media via Physics-Informed Neural Networks - AGU Publications
• Evaluating single multiplicative neuron models in physics-informed neural networks for differential equations - Nature
• Solving the Richards infiltration equation by coupling physics-informed neural networks with Hydrus-1D - Nature
• Reconstruction of excitation waves from mechanical deformation using physics-informed neural networks - Nature
• Implicit Stochastic Gradient Descent for Training Physics-Informed Neural Networks - The Association for the Advancement of Artificial Intelligence
• Analysis of pedestrian second crossing behavior based on physics-informed neural networks - Nature
• A framework for Li-ion battery prognosis based on hybrid Bayesian physics-informed neural networks - Nature
• Essential Review Papers on Physics-Informed Neural Networks: A Curated Guide for Practitioners - towardsdatascience.com
• Mixed formulation of physics-informed neural networks for thermo-mechanically coupled systems and heterogeneous domains - Wiley Online Library
• DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation - The Association for the Advancement of Artificial Intelligence
• Exploration on Physics-Informed Neural Networks on Partial Differential Equations (Student Abstract) - The Association for the Advancement of Artificial Intelligence
• Analyses of internal structures and defects in materials using physics-informed neural networks - Science | AAAS
• Modeling Non-Stationary Wind-Induced Fluid Motions With Physics-Informed Neural Networks for the Shallow Water Equations in a Polar Coordinate System - AGU Publications
• Probing the solar coronal magnetic field with physics-informed neural networks - Nature
• Accelerating Product Development with Physics-Informed Neural Networks and NVIDIA PhysicsNeMo - NVIDIA Developer
• Data-driven solutions and parameter estimations of a family of higher-order KdV equations based on physics informed neural networks - Nature
• Physics-Informed Neural Networks for Elliptical-Anisotropy Eikonal Tomography: Application to Data From the Northeastern Tibetan Plateau - AGU Publications
• Multi-level physics informed deep learning for solving partial differential equations in computational structural mechanics - Nature
• New insights into experimental stratified flows obtained through physics-informed neural networks - Cambridge University Press & Assessment
• Unraveling the Design Pattern of Physics-Informed Neural Networks: Part 06 - towardsdatascience.com
• The Old and the New: Can Physics-Informed Deep-Learning Replace Traditional Linear Solvers? - Frontiers
• Neural Oscillators for Generalization of Physics-Informed Machine Learning - The Association for the Advancement of Artificial Intelligence
• Physics-Informed Neural Networks (PINNs) for Wave Propagation and Full Waveform Inversions - AGU Publications
• Physics-informed machine learning - Nature
• Mean flow reconstruction of unsteady flows using physics-informed neural networks - Cambridge University Press & Assessment
• Discovering Differential Equations with Physics-Informed Neural Networks and Symbolic Regression - towardsdatascience.com
• Process-Informed Neural Networks: A Hybrid Modelling Approach to Improve Predictive Performance and Inference of Neural Networks in Ecology and Beyond - Wiley Online Library
• Using physics-informed derivative networks to solve the forward problem of a free-convective boundary layer problem - Nature
• Unraveling the Design Pattern of Physics-Informed Neural Networks: Part 04 - towardsdatascience.com
• Identifiability and predictability of integer- and fractional-order epidemiological models using physics-informed neural networks - Nature
• Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients | Scientific Reports - Nature
• Using Hybrid Physics-Informed Neural Networks for Digital Twins in Prognosis and Health Management - NVIDIA Developer
• Summer School “Physics-Informed Machine Learning for Geotechnical Engineering” – Applications Open - Politechnika Gdańska
• Modeling Water Flow and Solute Transport in Unsaturated Soils Using Physics-Informed Neural Networks Trained With Geoelectrical Data - AGU Publications
• Physics informed contour selection for rapid image segmentation - Nature
• Accelerating charge estimation in molecular dynamics simulations using physics-informed neural networks: corrosion applications - Nature
• Solving real-world optimization tasks using physics-informed neural computing | Scientific Reports - Nature